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🔍 Sliding Window – Java Cheat Sheet (One Page)

📌 What Is It?

Sliding Window is a technique to reduce time complexity for problems involving subarrays or substrings. Instead of nested loops, we “slide” a window across the input.

🧱 Pattern Template (Fixed Size)

int sum = 0;
for (int i = 0; i < nums.length; i++) {
    sum += nums[i];
    if (i >= k - 1) {
        max = Math.max(max, sum);
        sum -= nums[i - k + 1];
    }
}

🧱 Pattern Template (Variable Size)

int left = 0;
for (int right = 0; right < s.length(); right++) {
    // expand window by including s.charAt(right)

    while (window is invalid) {
        // shrink window from left
        left++;
    }

    if (window is valid) {
        // update result
    }
}

✅ Use Cases

• Maximum/Minimum sum of subarrays
• Substring with constraints (e.g., distinct chars)
• Smallest/Longest valid window
• Binary array with flips allowed

📘 Common LeetCode Problems

• 239. Sliding Window Maximum [Hard] Sliding Window, Monotonic Queue
• 727. Minimum Window Subsequence [Medium] Sliding Window, Two Pointers, DP
• 424. Longest Repeating Character Replacement [Medium] Sliding Window, HashMap
• 567. Permutation in String [Medium] Sliding Window, Two Pointers
• 340. Longest Substring with At Most K Distinct Characters [Medium] Sliding Window, HashMap
• 76. Minimum Window Substring [Hard] Sliding Window, HashMap
• 3. Longest Substring Without Repeating Characters [Medium] Sliding Window, HashMap

🧪 Example: Max Sum of Size k

int maxSum = 0, windowSum = 0;
for (int i = 0; i < nums.length; i++) {
    windowSum += nums[i];
    if (i >= k - 1) {
        maxSum = Math.max(maxSum, windowSum);
        windowSum -= nums[i - k + 1];
    }
}

🎬 Watch Minimum Window Subsequence Animation

🎬 Watch Sliding Window Maximum Animation

💡 Pro Tips

• Use two pointers (left & right) for variable-sized windows
• Carefully manage window conditions when shrinking
• Most problems can be solved in O(n) with a correct window